Machine Learning Data Analyst

Hello Heart

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تل ابيب - إسرائيل

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تاريخ النشر: نُشرت قبل 18 ساعة
عدد الوظائف الشاغرة: 1 عدد الوظائف الشاغرة

ملخص الوظيفة

About Hello Heart:

Hello Heart is on a mission to change the way people care for their hearts. The company provides the first app and connected heart monitor to help people track and manage their heart health. With Hello Heart users take steps to control their risk of heart attacks and stroke the leading cause of death in the United States. Peer-reviewed studies have shown that high-risk users of Hello Heart have seen meaningful drops in blood pressure cholesterol and even weight. Recognized as the digital leader in preventive heart health Hello Heart is trusted by more than 130 leading Fortune 500 and government employers national health plans and labor organizations. Founded in 2013 Hello Heart has raised more than $138 million from top venture firms and is a best-in-class solution on the American Heart Associations Innovators Network and CVS Health Point Solutions Management platform. Visit for more information.

About the role

Hello Heart is seeking a talented and motivated Machine Learning Data Analyst to join our Users Data Science team. As a Machine Learning Data Analyst you will be responsible for conducting in-depth analysis of our data science products from research to production. Your work will directly contribute to improving healthcare practices and enhancing the well-being of individuals.

Your responsibilities

  • Apply statistical analysis techniques data mining algorithms and visualization methods to extract meaningful patterns and trends from complex datasets.
  • Monitor & analyze our models performance in production generate insights and research leads for model improvements and new data driven solutions.
  • Conduct AB tests analyze the impact of models on users behavior taking into account cause/effect treatment/prevention relationships.
  • Collaborate closely with cross-functional teams including data scientists data engineers product managers and healthcare professionals to translate research findings into impactful digital solutions.
  • Stay updated with the latest research papers advancements and best practices in the field of healthcare analytics.

Your Skills

  • 2 years of hands-on experience as a Machine Learning Data Analyst/Data Scientist.
  • Strong analytical and critical thinking skills with the ability to interpret complex data and generate meaningful insights.
  • Proficiency in statistical analysis tools (e.g. R or Python with libraries like Pandas NumPy and SciPy) and data visualization techniques.
  • Strong knowledge and experience with SQL.
  • Familiarity with research methodologies experimental design and statistical modeling techniques (bayesian methods propensity score matching etc).
  • Experience in analyzing/testing the performance of ML models in production.
  • Bachelors degree in Statistics/Computer Science/Engineering or another related field.
  • Experience in recommendation systems user behavior segmentation conducting AB tests for ML models in production modeling the causal effects of treatment interventions - Advantage.




Hello Heart has a positive diverse and supportive culture - we look for people who are collaborative creative and courageous. Oh and if you want to see some recent evidence of the fun things we do at Hello Heart check out our Instagram page.


Required Experience:

IC

About Hello Heart:Hello Heart is on a mission to change the way people care for their hearts. The company provides the first app and connected heart monitor to help people track and manage their heart health. With Hello Heart users take steps to control their risk of heart attacks and stroke the le...
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المهارات المطلوبة

  • تحليلات البيانات
  • Microsoft Access
  • SQL
  • Power BI
  • R
  • Data Visualization
  • Tableau
  • إدارة البيانات
  • استخراج البيانات
  • SAS
  • Data Analysis Skills
  • التحليلات

عن الشركة

Company Logo

Hello Heart’s digital coaching app helps people manage heart health, and drives high employee engagement while potentially reducing medical claims costs.

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